Data Lake Management Platform – DataEz

It is estimated that data growth of organizations are expected to exponentially grow upto 42% by 2020 due to growing digitized and digital data. Though organizations have embraced Cloud to store and manage their growing data but very few have taken measures to stay equipped to meet the analytic demands to democratize data and to stay secured and compliant.

However, managing Data lake could be complicated as there are too many moving components, and the current best practices are prone to complex errors due to inflexibility and inscalability of the architecture to handle massive workloads. Reengineering such massive ecosystems is neither cost effective nor practical, if the focus is to maintain your market position.

Why and howDataEz is any day astep ahead thanyour datalake managementplatform?!

As the public cloud adoption grows, 8K Miles predicts that every organization will become a data company. This pushes them to have access to cutting edge security, self-cataloging data lake, automated data quality check, and be able to get insights from data on their own preferred tools. This means most organizations will turn into Data Organizations and will aggressively leverage data as a core asset to drive innovation in their businesses.

Technical and Monitoring controls to meet most compliance requirements.

Relies more on managed services so you focus more on use cases and applications.

Cloud Agnostic

Accelerators for all major cloud providers.

Core Data Lake Management Platform –DataEz Functionalities

Industries we serve

Healthcare &LifeSciences

Data lake and data analytics in healthcare is transforming the way the healthcare providers identify and treat illness, improve quality of life and avoid preventable deaths. The drive now is to understand as much as possible about a patient to facilitate diagnosing serious illness earlier to implement a simpler, less expensive treatment. To accomplish this task, a secured, cost optimized, and future-proof data ecosystem is essential.

The process of buying and selling is rapidly evolving on both online and offline channels, and data analytics plays a major role in this evolution. It has now become a vital part of every stage in the retail process from analyzing trends, predicting high demand products, forecasting where there will be high demand to optimizing price for a competitive edge. To perform these functions, any retail player will need access to new Artificial Learning and Machine Learning models.

Retail

Financial services

The applications of data go far beyond high-tech big-money trading. For example, data lake management and data analytics help financial institutions detect and prevent fraudulent transactions as well as provide trend analysis services for business growth. Financial institutes will need access to cutting edge security for data as well as scalable Artificial Intelligence and Machine Learning models to remain successful.